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Non-Linear Time Series Models in Emp...

Dijk, Dick van.

Non-Linear Time Series Models in Empirical Finance.

紀錄類型:	書目-電子資源 : 單行本
正題名/作者:	Non-Linear Time Series Models in Empirical Finance./
作者:	Franses, Philip Hans.
其他作者:	Dijk, Dick van.
出版者:	Cambridge :Cambridge University Press, : 2000.,
面頁冊數:	298 p.
標題:	Finance. -
電子資源:	Click here to view book
ISBN:	9780511754067 (electronic bk.)

Non-Linear Time Series Models in Empirical Finance.
Franses, Philip Hans.

Non-Linear Time Series Models in Empirical Finance.[electronic resource]. - Cambridge :Cambridge University Press,2000. - 298 p.

Cover; Half-title; Title; Copyright; Dedication; Contents; Figures; Tables; Preface; 1 Introduction; 2 Some concepts in time series analysis; 3 Regime-switching models for returns; 4 Regime-switching models for volatility; 5 Artificial neural networks for returns; 6 Conclusions; Bibliography; Author index; Subject index

The most up-to-date and accessible guide to one of the fastest growing areas in financial analysis by one of Europes's leading teaching and researching teams. This classroom-tested advanced undergraduate and graduate textbook provides an in-depth treatment of non-linear models, including regime-switching and artificial neural networks.

Electronic reproduction.

Available via World Wide Web.

Mode of access: World Wide Web.

ISBN: 9780511754067 (electronic bk.)Subjects--Topical Terms:

131585
Finance.
Index Terms--Genre/Form:

96803
Electronic books.

LC Class. No.: HG106 .F73 2000eb

Dewey Class. No.: 332/.01/5118

Non-Linear Time Series Models in Empirical Finance.
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505 0 $a Cover; Half-title; Title; Copyright; Dedication; Contents; Figures; Tables; Preface; 1 Introduction; 2 Some concepts in time series analysis; 3 Regime-switching models for returns; 4 Regime-switching models for volatility; 5 Artificial neural networks for returns; 6 Conclusions; Bibliography; Author index; Subject index
520 $a The most up-to-date and accessible guide to one of the fastest growing areas in financial analysis by one of Europes's leading teaching and researching teams. This classroom-tested advanced undergraduate and graduate textbook provides an in-depth treatment of non-linear models, including regime-switching and artificial neural networks.
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